Data Engineer (PH)

Taguig City, Metro Manila, Philippines / Malaysia / Indonesia

Data & AI & Risk – Risk & Data

Full‑time Employee – On‑site

Responsibilities

• Design, develop, and maintain highly scalable, reliable, and efficient data processing systems with a strong emphasis on code quality and performance.
• Collaborate closely with data analysts, software developers, and business stakeholders to deeply understand data requirements and architect robust solutions to address their needs.
• Focus on the development and maintenance of ETL pipelines, ensuring seamless extraction, transformation, and loading of data from diverse sources into our data warehouse based on Data‑bricks platform.
• Spearhead the development and maintenance of real‑time data processing systems utilizing cutting‑edge big data technologies such as Spark Streaming and Kafka.
• Establish and enforce rigorous data quality and validation checks to uphold the accuracy and consistency of our data assets.
• Act as a point of contact for troubleshooting and resolving complex data processing issues, collaborating with cross‑functional teams as necessary to ensure timely resolution.
• Proactively monitor and optimize data processing systems to uphold peak performance, scalability, and reliability standards, leveraging advanced AWS operational knowledge.
• Utilize AWS services such as EC2, S3, Glue and Data‑bricks to architect, deploy, and manage data processing infrastructure in the cloud.
• Implement robust security measures and access controls to safeguard sensitive data assets within the AWS environment.
• Stay abreast of the latest advancements in AWS technologies and best practices, incorporating new tools and services to continually improve our data processing capabilities.

Qualifications

• Bachelor’s or Master’s degree in Computer Science or a related field.
• Minimum of 5 years of hands‑on experience as a Data Engineer, demonstrating a proven track record of designing and implementing sophisticated data processing systems.
• Good understanding of Data‑bricks platform and Delta Lake.
• Familiar with data job scheduler tool such as Dagster.
• Proficiency in one or more programming languages such as Scala, Java, or Python.
• Deep expertise in big data technologies including Apache Spark for ETL processing and optimization.
• Proficient in utilizing BI tools such as Metabase for data visualization and analysis.
• Advanced understanding of data modeling, data quality, and data governance best practices.
• Outstanding communication and collaboration skills, with the ability to effectively engage with diverse stakeholders across the organization.
• Extensive experience in AWS operational management, including deployment, configuration, and optimization of data processing infrastructure within the AWS cloud environment.
• Strong understanding of AWS services such as EC2, S3, Glue and EMR, with the ability to architect scalable and resilient data solutions leveraging these services.
• Proficiency in AWS security best practices, with experience implementing robust security measures and access controls to protect sensitive data assets.
• Hands‑on experience with automation and DevOps tools such as Terraform for infrastructure as code and automation purposes.
• Can read/write in English.